Efficient and Green Embedding of Virtual Data Centers with Mixture of Unicast and Multicast Services

Chao Guo; Kai Xu; Sanjay Kumar Bose; Moshe Zukerman; Gangxiang Shen

doi:10.1109/TCC.2019.2897273

Efficient and Green Embedding of Virtual Data Centers with Mixture of Unicast and Multicast Services

Chao Guo
, Kai Xu
, Sanjay Kumar Bose
, Moshe Zukerman
, Gangxiang Shen

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

The improved efficiency achieved by virtualizing data centers (DCs) has been well established. In this paper, we propose a mixed Virtual Data Center (VDC) capable of supporting both unicast and multicast services. We provide a new method to realize the embedding of these VDCs. We also provide a Mixed Integer Linear Programming (MILP) formulation and a scalable heuristic algorithm for efficiently embedding its demands. Numerical results show that mixed VDC embedding supporting both unicast and multicast services performs significantly better than existing embedding methods in terms of system cost, power consumption, link capacity utilization, and VDC acceptance ratio.

Original language	English
Article number	8633411
Pages (from-to)	1008-1021
Number of pages	14
Journal	IEEE Transactions on Cloud Computing
Volume	9
Issue number	3
DOIs	https://doi.org/10.1109/TCC.2019.2897273
Publication status	Published - 1 Jul 2021
Externally published	Yes

Keywords

Data center
multicast
unicast
virtual data center

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10.1109/TCC.2019.2897273

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title = "Efficient and Green Embedding of Virtual Data Centers with Mixture of Unicast and Multicast Services",

abstract = "The improved efficiency achieved by virtualizing data centers (DCs) has been well established. In this paper, we propose a mixed Virtual Data Center (VDC) capable of supporting both unicast and multicast services. We provide a new method to realize the embedding of these VDCs. We also provide a Mixed Integer Linear Programming (MILP) formulation and a scalable heuristic algorithm for efficiently embedding its demands. Numerical results show that mixed VDC embedding supporting both unicast and multicast services performs significantly better than existing embedding methods in terms of system cost, power consumption, link capacity utilization, and VDC acceptance ratio.",

keywords = "Data center, multicast, unicast, virtual data center",

author = "Chao Guo and Kai Xu and Bose, \{Sanjay Kumar\} and Moshe Zukerman and Gangxiang Shen",

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year = "2021",

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AU - Guo, Chao

AU - Xu, Kai

AU - Bose, Sanjay Kumar

AU - Zukerman, Moshe

AU - Shen, Gangxiang

PY - 2021/7/1

Y1 - 2021/7/1

N2 - The improved efficiency achieved by virtualizing data centers (DCs) has been well established. In this paper, we propose a mixed Virtual Data Center (VDC) capable of supporting both unicast and multicast services. We provide a new method to realize the embedding of these VDCs. We also provide a Mixed Integer Linear Programming (MILP) formulation and a scalable heuristic algorithm for efficiently embedding its demands. Numerical results show that mixed VDC embedding supporting both unicast and multicast services performs significantly better than existing embedding methods in terms of system cost, power consumption, link capacity utilization, and VDC acceptance ratio.

AB - The improved efficiency achieved by virtualizing data centers (DCs) has been well established. In this paper, we propose a mixed Virtual Data Center (VDC) capable of supporting both unicast and multicast services. We provide a new method to realize the embedding of these VDCs. We also provide a Mixed Integer Linear Programming (MILP) formulation and a scalable heuristic algorithm for efficiently embedding its demands. Numerical results show that mixed VDC embedding supporting both unicast and multicast services performs significantly better than existing embedding methods in terms of system cost, power consumption, link capacity utilization, and VDC acceptance ratio.

KW - Data center

KW - multicast

KW - unicast

KW - virtual data center

UR - https://www.scopus.com/pages/publications/85114490381

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M3 - Article

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JO - IEEE Transactions on Cloud Computing

JF - IEEE Transactions on Cloud Computing

IS - 3

M1 - 8633411

ER -

Efficient and Green Embedding of Virtual Data Centers with Mixture of Unicast and Multicast Services

Abstract

Keywords

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